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利用虚拟筛选和生物分子模拟鉴定新型登革热病毒 NS2B/NS3 蛋白酶潜在抑制剂。

Identification of novel and potential inhibitors against the dengue virus NS2B/NS3 protease using virtual screening and biomolecular simulations.

机构信息

Medical Research Center, the Second Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.

Department of Biochemistry, Abdul Wali Khan University, Mardan, KPK, Pakistan.

出版信息

Int J Biol Macromol. 2024 Jun;272(Pt 1):132855. doi: 10.1016/j.ijbiomac.2024.132855. Epub 2024 Jun 2.

Abstract

Approximately 3.9 billion individuals are vulnerable to dengue infection, a prevalent cause of tropical diseases worldwide. Currently, no drugs are available for preventing or treating Flavivirus diseases, including Dengue, West Nile, and the more recent Zika virus. The highly conserved Flavivirus NS2B-NS3 protease, crucial for viral replication, is a promising therapeutic target. This study employed in-silico methodologies to identify novel and potentially effective anti-dengue small molecules. A pharmacophore model was constructed using an experimentally validated NS2B-NS3 inhibitor, with the Gunner Henry score confirming the model's validity. The Natural Product Activity and Species Source (NPASS) database was screened using the validated pharmacophore model, yielding a total of 60 hits against the NS2B-NS3 protease. Furthermore, the docking finding reveals that our newly identified compounds from the NPASS database have enhanced binding affinities and established significant interactions with allosteric residues of the target protein. MD simulation and post-MD analysis further validated this finding. The free binding energy was computed in terms of MM-GBSA analysis, with the total binding energy for compound 1 (-57.3 ± 2.8 and - 52.9 ± 1.9 replica 1 and 2) indicating a stronger binding affinity for the target protein. Overall, this computational study identified these compounds as potential hit molecules, and these findings can open up a new avenue to explore and develop inhibitors against Dengue virus infection.

摘要

大约有 39 亿人易感染登革热,这是一种全球流行的热带病。目前,还没有药物可用于预防或治疗黄病毒病,包括登革热、西尼罗河热和最近的寨卡病毒。高度保守的黄病毒 NS2B-NS3 蛋白酶对病毒复制至关重要,是一个很有前途的治疗靶点。本研究采用计算机模拟方法来鉴定新的、有潜力的抗登革热小分子。使用经实验验证的 NS2B-NS3 抑制剂构建药效团模型,Gunner Henry 评分验证了模型的有效性。使用验证后的药效团模型筛选天然产物活性和物种来源 (NPASS) 数据库,共得到针对 NS2B-NS3 蛋白酶的 60 个命中物。此外,对接结果表明,我们从 NPASS 数据库中鉴定的新化合物与靶蛋白的变构残基具有增强的结合亲和力和显著的相互作用。MD 模拟和 MD 后分析进一步验证了这一发现。根据 MM-GBSA 分析计算自由结合能,化合物 1 的总结合能(-57.3 ± 2.8 和-52.9 ± 1.9 副本 1 和 2)表明对靶蛋白具有更强的结合亲和力。总的来说,这项计算研究鉴定了这些化合物作为潜在的命中分子,这些发现为探索和开发抗登革热病毒感染抑制剂开辟了新途径。

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